This thesis aims to explore the determinants of corporate default in the UK industrial
companies and propose the best performing probability of default measurement.
we re-examine some of the most popular probability of default models in the literature
(Altman's Z-Score and Olson's O-Score) and define a hybrid model (H-Score),
estimated from a dynamic legit model using accounting and market variables. Our
Z-Score and O-Score results update many of the original covariate values proposed by
above authors. Various performance test analysis show that H-Score provides the most
information about the probability of default for our UK dataset.
These various probability of default measurements arc then applied as the proxy
of distress risk to examine the empirical analysis of distress risk premium in the UK
context, mainly documented as a negative risk premium in US studies. We follow the
latest development in this literature (Campbell et al (2008) and Chen et al. (2010)
and carry out portfolio analysis to test the hypothesis of whether financially more distressed
firms are rewarded by higher returns. Our results provide mixed findings. The
existence of distress risk premium puzzle depends on many factors, including the way
we construct the distressed p0l1folios and the selection of probability of default measurement
as a proxy of distress risk.
Finally, we twist our credit risk analysis to consider credit risk spillover effect
and provide a measure of the risk-spillover connectedness within European investment
banking system. We use the methodology advanced by Diebold and Yilmaz
(2009,2013) and Greenwood-Nimmo el al. (2013) and apply the Vector Autoregression
(VAR) model and Forecast Error Variance Decomposition (FE VD) to the credit
default spread (CDS) data of the most liquid and actively traded nine European investment
banks. Our various connectedness measurement results indicate that the
inter-connectedness among European investment banks are extremely dynamic due to
individual bank's idiosyncratic risk factors and the wider macroeconomic situations.
Hence, supervisory institutions need la understand the time-varying dynamic nature of
the connectedness among banks and be prepared to adjust policies to prevent accelerating
of the systemic risk.